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Visualization Methods Overview Presentation Cambridge University Eppler September 2006
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Visualization Methods Overview Presentation Cambridge University Eppler September 2006

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Lesson taught at Cambridge in the Engineering & Manufacturing tripod program.

Lesson taught at Cambridge in the Engineering & Manufacturing tripod program.

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Visualization Methods Overview Presentation Cambridge University Eppler September 2006 Visualization Methods Overview Presentation Cambridge University Eppler September 2006 Presentation Transcript

  • The Visualization SpectrumA Systematic Overview of Visualisation Methods for Managers
    Martin J. Eppler
    University of Lugano (USI)
    www.knowledge-communication.org / www.lets-focus.com
    Martin.Eppler@gmail.com
    Cambridge, IfM, September 28th 2006
  • VisualizationMethodsforManagement:OurOverview
  • Outline
    The Realm of Visualization
    Visualization Classifications
    An Activity-based View
    How to choose the right Method
    Conclusion
    :
  • The ABC of Visualization
    Size
    Color/ Texture
    .
    .
    Position
    Animation
    Orientation
    Form
    Source: adapted from J. Bertin
  • Accuracy Ranking of Quantitative Perceptual Tasks
    Position
    More
    Accurate
    Length
    Angle
    Slope
    Area
    Less
    Accurate
    Volume
    Color
    Density
    Source: Mackinlay 88 from Cleveland & McGill
  • Emprical Results: Use of visualization in management
    -> Quantitative charts dominate, what about conceptual visualization?
    Source: Meier, 1994
  • Overview of Quantitative Diagrams
    Source: www.corda.com; Howard Wainer, 2001
  • Diagram
    Types
    (static)
    Structure
    TimeSeries
    Phases / Steps
    Relationships
    (dynamic)
    Process
    Clustering/
    Positioning
    cyclical
    continuous
    linear
    linear
    hierarchical
    Network
    Venn
    Matrix
    Coordinates
    t
    Timeline Process Cycle Spectrum Pyramid Network Venn Matrix Cartesian
    Overview of NineSimple Qualitative Business Diagrams
  • General Visualization Conventions
    • Time is shown from the left to right.
    • Important aspects are represented with larger shapes, stronger colors that indicate higher importance.
    • The pattern of grouping distinguishes between central and secondary information.
    • The arrangement corresponds to logical flow.
    • Proximity implies similarity, distance suggests differences
    • Identical shapes or colors designate identical types of objects (visualize different things differently)
    A
    B
    Source: adapted and expanded from Rhodes, 1991, p. 135.
  • Outline
    The Realm of Visualization
    Visualization Classifications
    An Activity-based View
    How to choose the right Method
    Conclusion
    :
  • Kosslyn’s Classification:Types of Symbolic Displays
    • Framework
    • sets the stage
    • kinds of measurements, scale, ...
    • Content
    • marks
    • point symbols, lines, areas, bars, …
    • Labels
    • title, axes, tic marks, ...
    Graphs
    Charts
    Maps
    Diagrams
  • An Empirical Taxonomy: Lohse et al. 1994
    structure diagrams: description of physical object
    cartograms: spatial maps showing quantitative data
    maps: symbolic representation of physical geography
    graphic tables
    process diagrams
    icons: e.g., logos
    time charts: e.g., Gantt charts
    network charts: flow chart, org chart, decision trees, pert tree
    photo-realistic pictures
    tables: single to multiple rows
    graphs: quantitative information using position and magnitude of geometric objects. 1-3D, examples: cartesian or polar coordinate system: scatterplots, line bar, pie chart, Chernoff face graphs)
  • Horn´s elements of Visual Language
  • Other Taxonomies
    Shneiderman (1996) proposes a task by data type taxonomy of information visualization with seven data types:
    one-, two-, three-dimensional data,
    temporal and multi-dimensional data,
    tree and network data
    and seven tasks (overview, zoom, filter, details-on-demand, relate, history, and extracts).
    Card, et al., 1998) constructed a data-oriented taxonomy for information visualization techniques, which is based on Card and MacKinlay (1997): This taxonomy divides the field of visualization into several subcategories:
    Scientific Visualization,
    GIS,
    Multi-dimensional Plots,
    Multi-dimensional Tables,
    Information Landscapes and Spaces,
    Node and Link,
    Trees,
    Text Transforms
  • Outline
    The Realm of Visualization
    Visualization Classifications
    An Activity-based View
    How to choose the right Method
    Conclusion
    :
  • The KnowViz Framework (Eppler & Burkhard 2005)
  • Examples of the seven Types
    Envisioning: mental imagery, thinking aloud
    Sketching: doodling, flip charting
    Expressing: visual metaphor, cartoon
    Diagramming: Gantt chart, Toulmin chart
    Mapping: geographic map, knowledge map
    Materializing: Lego serious play, Compad
    Exploring: treemap, parallel coordinates
  • 1. Examples of Envisioning
    Verbal Metaphors: ‚Backwardparking‘
    Analogies: Benzol ring invention
    Parables: The Elephantandthe 4 blind man
    Simulation: Mentallyvisualizing an activity.
  • 2. Examples of Sketching
  • 3. Examples of Expressing: Visual Metaphor
  • 3. Examples of Expressing: Cartoons
  • 4. Examples of Diagramming
  • 5. Examples of Mapping
  • 6. Examples of Materializing
  • 7. Examples of Exploring
  • Comparative Description of each Activity Type
    +
    -
  • Outline
    The Realm of Visualization
    Visualization Classifications
    An Activity-based View
    How to choose the right Method
    Conclusion
    :
  • When to use which quantitative chart type?
    Line graph
    x-axis requires quantitative variable
    Variables have continuous values
    familiar/conventional ordering among ordinals
    Bar graph
    comparison of relative point values
    Scatter plot
    convey overall impression of relationship between two variables
    Pie Chart?
    Emphasizing differences in proportion among a few numbers
  • When to use which map?(Small, 1999)
  • Selecting the right Visualization Activity
    = i.e., Iceberg risk metaphor
    = i.e., scenario sketching
    = i.e., Gantt chart for project
  • The visualization spectrum contains quantitative and qualitative visualization formats.
    They can be used to depict structures or processes.
    In order to choose the right method, think about its main purpose, the content type, the target audience and communication situation.
    Conceive of visualization as an activity and choose among envisioning, sketching, ex-pressing, diagramming, mapping, materializing or exploring.
    !
    Conclusion
  • Great Books on Visualization
  • Further References
    • Bertin, J. (1974). The Semiologyof Graphics. Diagrams Networks, Maps.
    • Sachs-Hombach, K. (2005). Bildwissenschaft / Image Sciences.
    • Eppler, M. (2006) Managing Information Quality: Increasingthe Value of Information in knowledge-intensive Products andProcesses, 2nd ext. Edition.
    • Eppler, M. (2003) The Image of Insight: Using Visual MetaphorstoCommunicateKnowledge, in Journal of Universal Computer Science
    • Eppler, M. (2002) Making Knowledge Visible throughKnowledgeMaps, in: Holsapple (Ed.): Knowledge Management Handbook
    • M. Peterson (1995) Interactive and Animated Cartography
    • Eppler, M., Sukowski, O. (2000) Managing Team Knowledge, in: European Management Journal, June, Oxford.
    • Eppler, M. (2006) A comparison between concept maps, mind maps, conceptual diagrams and visual metaphors. In: Information Visualization, September Issue.
    • Eppler, M. (1999) Conceptual Management Tools, NetAcademy Press. Online at: www.analyst-academy.org & www.knowledge-communication.org
    • Galloway, D. (1994) : Mapping Work Processes
    • Horn, R.E. (1998) Visual Language. Global Communication for the 21st Century
    • Horn, R. (1989): Mapping Hypertext
    • Huff, A.(1990) Mapping Strategic Thought
    • Huff, A. (2001) Mapping Strategic Knowledge
    • Probst, G., Deussen, A., Eppler, M., Raub, S. (2000): Kompetenz-Management
    • Wurman, R. Information Architects, 1996
    • Wurman, R. Information Anxiety2, 2001
    Visualization
    Overview
    Visual
    Metaphors
    Knowledge
    Maps
    Diagrams